Wireless communication networks continue to evolve with enhanced and new features being developed for deployment in the current and future generation networks. One particular area of development resides in the area of positioning a mobile station within a wireless network quickly, with high accuracy, and with nominal network traffic. This positioning feature is being required in future networks to provide emergency E911 calls, with specifications requiring positioning to an accuracy of under 10 meters. Positioning of mobiles is also finding advantages in the area of providing position on demand in commercial applications, such as in fleet management for rental car fleets, and the mobile user being able to obtain position on demand to aid in navigation and so forth.
Positioning of a mobile station is particularly difficult due to a number of factors. Terrestrial positioning is encumbered due to multipath and fading of signals, thereby making simple triangulation measurements unreliable for high accuracy calculations. Time of arrival (TOA) techniques measure the received time of synchronized signals broadcast from various points, such as base transceiver stations (BTSs), with the TOA information being provided back to a network node, such as a mobile switching center (MSC) to roughly determine the position of a mobile. Again, due to multipath and signal fading, TOA techniques can only generally provide the position of a mobile station, and will not necessarily meet the high resolution requirements of future applications, such as enhanced emergency E911 calls and navigation systems.
Global positioning system (GPS) receivers are one viable solution to providing a position of a mobile station with high accuracy. The GPS is one solution to meet the positioning requirement in a global system for mobiles (GSM) based network. The GPS meets the requirements of both the FCC-mandated E911 service, as well as other market-driven applications. GPS is based on a constellation of satellites launched by the US Government beginning in 1978. It is a well known technology that has been used in many military and civilian applications.
Most commercially available, standalone GPS receivers operate in a continuous navigation mode. In this mode, the receiver performs psuedorange measurements on a periodic (e.g., one second) and inputs these measurements to a processing algorithm such as a Kalman filter. The Kalman filter takes into account both the statistics of the measurements and the current state of the receiver dynamics to compute a new state estimate with minimum error variance. This approach is advantageous for navigation applications because of the availability of the continuously updated receiver state estimate (e.g., position/velocity/acceleration). Another advantage is that the Kalman filter can propagate the current state when unacceptable or insufficient measurements are available. This is especially helpful for a GPS receiver in an environment with intermittent obstructions to the signal.
However, continuous GPS navigation using an algorithm such as a Kalman filter requires that the receiver be operating continuously or for at least some duty cycle of the update period. The power consumption for this continuous mode may not be acceptable for battery-powered applications such as a GPS in a mobile communication handset. For these applications, there is desired another receiver mode known as position-on-demand. In this mode, the mobile communication handset may request and receive any necessary GPS assistance information from a remote source, acquire the satellite signals and perform pseudorange measurements, and then compute the position estimate, and return it to the remote requestor. Subsequently, the handset puts the GPS receiver into a "sleep" mode until another positioning action is necessary. For a GPS receiver integrated into a mobile communication handset, this position-on-demand mode has a much smaller impact on talk and standby times than the continuous navigation mode.
In a position-on-demand mode, the handset needs GPS assistance information to speed up the search procedure of the GPS receiver due to the motion of satellites relative to the GPS receiver, and vice versa. The duration of the GPS positioning process is directly dependent on how much information the GPS receiver has. Most GPS receivers are programmed with almanac data, which coarsely describes the satellite positions and it is applicable for one year. If the receiver has a real time clock that is reasonably accurate, then it can compute the approximate positions of the satellites at any given time.
However, this information is not sufficient for a position solution. If the GPS receiver does not have some "a priori" knowledge of its approximate location, then it does not know which satellites are visible and their approximate ranges. In this case, the receiver must search the entire length of the Gold code for each satellite. This search procedure is even more difficult due to the motion of the satellites relative to the receiver. The apparent Doppler frequency depends on how much of the motion is along the line of the sight from receiver to satellite, and is in the range of +/-4 kHz in most areas. The search for each satellite must be across all possible code phases and Doppler frequencies, as shown at 10 in FIG. 1. In some modern GPS receivers, the time-to-fix is up to ten minutes.
The time-to-fix can be reduced substantially if the GPS receiver has up-to-date ephemeris and clock correction information. Ephemeris provides a highly accurate model of the satellite motion over a period of two hours, but is much less accurate thereafter. In addition, the time-to-fix can be substantially reduced if the receiver can use the last computed position as an estimate for its current position. The validity of this assumption depends on the user mobility and the time since the last position fix, but in general provides a reasonable starting point for most nonairborne applications. In addition, the accuracy of the receiver's time reference must not have degraded more than a few seconds since the last position fix. Thus, the receiver needs an accurate frequency source.
If all of these conditions are met, then the GPS receiver can compute accurate estimates of the visible satellites and the respective propagation delays (code phases) and Doppler frequencies. This information focuses the correlation search as shown at 12 in FIG. 1, and allows the GPS receiver to compute a position very quickly. A time-to-fix of only a few seconds is feasible for most modern GPS receivers.
Unfortunately, these conditions cannot be met for standalone GPS receivers in all situations. However, a GPS receiver integrated into a mobile station (GPS-MS) can benefit greatly from a network communication link, such as a personal communication service (PCS) communication link. Time and position estimates, as well as satellite ephemeris and clock information, must be provided in a timely manner by the communication network. The frequency accuracy of GSM networks is very good, and can help the GPS-MS to focus the search along the Doppler axis of FIG. 1.
There are several requirements on the wireless network in order to support assisted-GPS positioning. Several methods of providing assisted-GPS positioning are being considered, with the requirement that the methodology not be particularly onerous and generate a large amount of network traffic.
There is desired an assisted-GPS positioning communication system and methodology that provides positioning of mobile stations with a GPS receiver (GPS-MS) that requires nominal network traffic, and that provides a fast and accurate positioning service.